Download Inherited or earned? Performance of foreign banks in Central

No 2008 – 16
September
Inherited or earned? Performance of foreign
banks in Central and Eastern Europe
_____________
Olena Havrylchyk, Emilia Jurzyk
Inherited or earned? Performance of foreign
banks in Central and Eastern Europe
Olena Havrylchyk, Emilia Jurzyk
No 2008 – 16
Septembre
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
TABLE OF CONTENTS
1. Introduction
8
2. Related literature
11
3. Methodology
12
4. Description of the data
16
5. Descriptive statistics and evidence of the selection bias
18
6. Propensity score matching to control for the selection bias
20
7. Results from the difference-in-difference analysis on the matched sample 24
8. Additional robustness checks
31
9. Conclusions
34
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CEPII, Working Paper No 2008 – 16
I NHERITED OR EARNED ? P ERFORMANCE OF FOREIGN BANKS IN C ENTRAL AND
E ASTERN E UROPE
N ON - TECHNICAL S UMMARY
Foreign acquisitions of banks since the 1990s have substantially altered the financial landscape and governance of banks in many transition and developing countries. As of end-2006,
foreign banks accounted for more than 39 percent of total banking assets in developing countries. Such a transformation has given rise to a large literature that analyzes the impact of foreign bank ownership and mode of entry on banks’ performance, measured by x-efficiency, net
interest margin, lending rates, profitability, profit-efficiency, and loan growth. However, there
is a striking lack of studies that look at the qualities of banks that were acquired by foreign
investors. This is particularly surprising because if foreign banks acquire institutions in developing countries that possess certain characteristics, the standard results of post-acquisition
performance are biased.
The hypothesis that selection bias exists - as only banks with certain characteristics were
taken over - is supported by evidence, but the direction of this bias often depends on the region. In general, we can plausibly assume that foreign investor would prefer to acquire more
profitable and healthier banks with high market power. On the other hand, in many countries
the authorities were skeptical towards foreign investors and allowed foreign acquisition of
only failing institutions. Very often entry barriers were loosened only in the wake of crises
and this was motivated by the need to recapitalize and reestablish a functioning banking system.
In the present paper we propose to use a combination of propensity score matching and
difference-in-difference techniques to analyze the impact of bank acquisition by foreign investors controlling for a possible selection bias. We apply this methodology to a dataset
comprising 352 banks from 11 Central and Easter European countries (CEECs) between
1993-2005. Our empirical strategy yields a number of interesting results. We show that
foreign investors did not acquire banks at random, but chose institutions with large market
power. Moreover, the acquired banks were often in poor financial condition. Controlling for
this selection bias, we find a positive impact of foreign bank ownership on acquired banks’
performance, as well as on their market power. We show that during three years after the
takeover, banks have become more profitable due to cost minimization and better risk management. They have additionally gained market share, because they passed their lower cost of
funds to borrowers in terms of lower lending rates. Our methodology offers us also a unique
possibility to track the dynamics of banks’ post-acquisition performance. We show that while
the changes in profitability appear one year after the acquisition, market share increases only
one period later. In total, the results of our analysis lead us to believe that previous studies failed to pick up these improvements in banks’ performance because they assumed that
acquisitions were done randomly.
4
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
A BSTRACT
Using a combination of propensity score matching and difference-in-difference techniques
we investigate the impact of foreign bank ownership on the performance and market power of
acquired banks operating in Central and Eastern Europe. This approach allows us to control
for selection bias as larger but less profitable banks were more likely to be acquired by foreign
investors. We show that during three years after the takeover, banks have become more
profitable due to cost minimization and better risk management. They have additionally
gained market share, because they passed their lower cost of funds to borrowers in terms of
lower lending rates. Previous studies failed to pick up the improvements in performance of
takeover banks, because they did not account for the performance of financial institutions
before acquisitions.
JEL Classification: G15, G21, G34, F36
Keywords: foreign banks, foreign acquisition, propensity score matching
5
CEPII, Working Paper No 2008 – 16
H ÉRITÉE OU MÉRITÉE ? L A PERFORMANCE DES BANQUES ÉTRANGÈRES EN
E UROPE CENTRALE ET ORIENTALE
R ESUME NON TECHNIQUE
Les acquisitions étrangères des banques depuis les années 1990 ont sensiblement changé le
paysage financier et la gouvernance des banques dans beaucoup de pays en transition et en
développement. Fin 2006, les banques étrangères représentaient plus de 39 pour cent des actifs bancaires totaux dans les pays en développement. Cette transformation a donné lieu à
une importante littérature qui analyse l’impact de la propriété bancaire étrangère et du mode
d’entrée sur la performance des banques, mesurés par l’efficience X, la marge nette d’intérêt,
les taux débiteurs, la rentabilité, et la croissance des prêts. Cependent, ces études ne tiennent
pas compte de la qualité des banques rachetées par les investisseurs étrangers. Cela est particulièrement étonnant parce que si les banques étrangères rachètent des institutions possédant
certaines caractéristiques, les résultats traditionnels sont biaisés.
L’hypothèse d’un biais de sélection - puisque seules les banques possédant certaines caractéristiques étaient reprises - est démontrée, mais le sens de ce biais dépend souvent de la
région. En général, nous pouvons supposer que l’investisseur étranger préférerait acquérir
des banques plus rentables et plus saines ayant un pouvoir du marché élevé. Néanmoins,
dans beaucoup de pays les autorités étaient sceptiques envers les investisseurs étrangers et
ont seulement permis l’acquisition des institutions défaillantes. Les obstacles à l’entrée n’ont
très souvent été levés qu’à la suite de crises et cela a été motivé par le besoin de recapitaliser
les banques et de rétablir un système bancaire opérationnel.
Dans cet article, nous proposons d’utiliser une combinaison de techniques d’appariement sur
la base d’un score de propension (propensity score matching) et de doubles différences pour
analyser l’impact de l’acquisition bancaire par les investisseurs étrangers tout en contrôlant
le biais de sélection. Nous appliquons cette méthodologie à un ensemble de données comportant 352 banques de 11 pays d’Europe centrale et orientale entre 1993-2005. Notre stratégie
empirique nous permet d’obtenir un certain nombre de résultats intéressants. Nous montrons
que les investisseurs étrangers n’ont pas acquis des banques au hasard, mais ont choisi des
institutions ayant un grand pouvoir du marché. En outre, les banques rachetées se trouvaient
souvent en mauvaise situation financière. Contrôlant ce biais de sélection, nous trouvons un
impact positif de la propriété bancaire étrangère sur la performance acquise des banques,
ainsi que sur leur pouvoir du marché. Nous montrons que pendant trois ans après leur rachat,
les banques sont devenues plus rentables grâce à une réduction des coûts et une meilleure
gestion des risques. Elles ont en outre gagné des parts de marché, parce qu’elles ont transmis
leur plus faible coût de financement aux emprunteurs à travers des taux débiteurs plus faibles.
Notre méthodologie nous offre également une possibilité unique de suivre la dynamique de
la performance après acquisition. Nous montrons que tandis que les changements dans la
rentabilité apparaissent un an après l’acquisition, les parts de marché augmentent seulement
un an plus tard. Au total, nos résultats nous amènent à penser que, si les études précédentes
n’ont pas montré ces améliorations de la performance des banques, c’est parce qu’elles ont
supposé que les acquisitions ont été faites au hasard.
6
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
R ESUME COURT
Utilisant une combinaison de techniques d’appariement sur la base d’un score de propension
(propensity score matching) et de doubles différences, nous étudions l’impact de la propriété
bancaire étrangère sur la performance et le pouvoir de marché des banques en Europe centrale
et orientale. Cette approche nous permet de contrôler le biais de sélection selon lequel les
banques les plus grandes mais aussi les moins rentables sont davantage susceptibles d’être
acquises par les investisseurs étrangers. Nous montrons que pendant trois ans après le rachat,
les banques sont devenues plus rentables en raison de la réduction des coûts et d’une meilleure
gestion des risques. Elles ont en outre gagné des parts de marché, parce qu’elles ont transféré
leur faible coût de financement aux emprunteurs en termes de plus faibles taux débiteurs.
Les études précédentes n’ont pas réussi à montrer l’amélioration des résultats des banques
rachetées, parce qu’elles n’ont pas pris en compte la performance des institutions financières
avant les acquisitions.
Classification JEL : G15, G21, G34, F36
Mots clés : banques étrangères, acquisition étrangère, appariement sur la base d’un score de
propension.
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CEPII, Working Paper No 2008 – 16
I NHERITED OR EARNED ? P ERFORMANCE OF FOREIGN BANKS IN
C ENTRAL AND E ASTERN E UROPE
Olena H AVRYLCHYK 1 2
Emilia J URZYK3
1.
I NTRODUCTION
Foreign acquisitions of banks since the 1990s have substantially altered the financial landscape and governance of banks in many transition and developing countries.
As of end-2006, foreign banks accounted for more than 39 percent of total banking
assets in developing countries. Their presence is particularly important in Central
and Eastern Europe, Latin America, and Sub-Saharan Africa where more than 50
percent of local banking markets are controlled by foreign investors. Such a transformation has given rise to a large literature that analyzes the impact of foreign bank
ownership and mode of entry on banks’ performance, measured by X-efficiency, net
interest margin, lending rates, profitability, profit-efficiency, and loan growth. However, there is a striking lack of studies that look at the qualities of banks that were
acquired by foreign investors. This is particularly surprising because if foreign banks
acquire institutions in developing countries that possess certain characteristics, the
standard results of post-acquisition performance are biased.
The hypothesis that selection bias exists - as only banks with certain characteristics
were taken over - is supported by evidence, but the direction of this bias often depends
on the region. In general, we can plausibly assume that foreign investor would prefer
to acquire more profitable and healthier banks with high market power. Moreover,
some authorities preferred to recapitalize and clean up portfolios of target banks in
order to make them more attractive for foreign investors, which was the case of par1
CEPII ([email protected]).
We are particularly grateful to De Haas & Van Lelyveld (2006) for providing us with the information on foreign bank ownership. We are also grateful to Nikolay Nenovsky and Lyubomir Mirchev
(Bulgarian National Bank), Maire Otsus (The Financial Supervision Authority of the Bank of Estonia),
Dobromil Serwa and Sylwester Kozak (National Bank of Poland), Florian Neagu (National Bank of
Romania), Evan Kraft (Croatian National Bank), Elmars Zakulis (National Bank of Latvia), Róbert
Szegedi (National Bank of Hungary), Loreta Sprindziunaite (National Bank of Lithuania), Tomas Rydl
(Czech National Bank), and Hendrich Datel (National Bank of Slovakia) for providing us information
on state ownership of banks.
3
Department of Economics and LICOS K.U.Leuven ([email protected]). Emilia
Jurzyk would also like to gratefully acknowledge the financial support from the Research Council of
the KU Leuven, in the framework of Central and Eastern European Initiatives. The usual disclaimer
applies.
2
8
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
tial bank privatization in China. On the other hand, in many countries the authorities
were skeptical towards foreign investors and allowed foreign acquisition of only failing institutions, like in Poland. Very often entry barriers were loosened only in the
wake of crises and this was motivated by the need to recapitalize and reestablish a
functioning banking system. This was the case of Baltic and Balkan countries after the Russian crisis, Argentina after Mexico’s tequila crisis, and many East Asian
countries following their 1997-98 financial crises.
The existence of a selection bias has crucial implications for the analysis of postacquisition performance of financial institutions. For instance, if foreign banks acquire institutions with deteriorating financial stance - like it happened in most of
the Central and Eastern Europe - the standard regression methods of analyzing the
post-takeover performance would result in downward-biased estimates. This, in turn,
would explain a consistent lack of empirical evidence on the benefits of foreign acquisition in developing countries. Existing studies demonstrate that foreign banks are
more efficient and profitable than domestic institutions, and they experience faster
and more stable loan growth. A closer examination reveals, though, that the mode
of foreign bank entry plays an important role, as we only observe superior performance of institutions that have been newly established. At the same time, there is
no evidence that the performance of banks that were acquired by foreign investors is
superior to domestic ones (Bonin, Hasan & Wachtel (2005); Martinez Peria & Mody
(2004); Claeys & Hainz (2007); De Haas & Van Lelyveld (2006); Havrylchyk &
Jurzyk (2007)). Without this proof, the results obtained for greenfield institutions
cannot be entirely attributed to benefits of foreign ownership but rather raise suspicion that they merely reflect a different borrower mix, with a higher share of large
and transparent clients at the expense of small and medium enterprises.
In the present paper we propose to use a combination of propensity score matching and difference-in-difference (DID) techniques to analyze the issues raised above.
This is a new methodology in the area of bank performance research, which is borrowed from other fields of economics, namely labor and firm performance. Recently,
this methodology has also been used in banking studies, but it was applied to firm
level data, and we believe that our study is the first one to apply it to bank level data.
The main purpose of our analysis is to compare banks that were acquired by foreign investors with comparable domestic banks that have stayed in domestic ownership during the analyzed period. In order to determine “comparable ” banks we
use propensity score matching, which implies running a logistic regression, where
a probability of a bank being acquired is a function of observable bank and country
characteristics. This allows us to assign to each bank a probability of being acquired
and then to match foreign banks with domestic banks that are the “closest” in terms
of the propensity score. In the second step, we compare the performance of acquired
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CEPII, Working Paper No 2008 – 16
bank with the matched domestic bank. To do so we rely on difference-in-difference
technique as it allows us to take into account non-observable pre-acquisition differences that we were not able to control for in the first step. We apply this methodology
to a dataset comprising 352 banks from 11 Central and Easter European countries
(CEECs) between 1993-2005. Since this region recorded the highest inflow of foreign direct investment into the banking system in the world and we were able to
indentify 77 cross-border acquisitions, we believe it presents an excellent laboratory
to perform such a study.
In our analysis of post-acquisition behavior of banks, we focus on the possible tradeoff between performance and market power of banks. This is an important issue,
because foreign bank ownership has gone hand in hand with higher market concentration. Moreover, foreign banks have contributed to this development directly by acquiring and merging domestic institutions, or by motivating smaller domestic banks
to merge in the face of increased competition (Martinez Peria & Mody (2004); Lanine & Vander Vennet (2007)). If banks with large market power can set prices that
are less favorable to consumers and earn abnormal profits, this should raise concerns
about the competition on the market (relative-market-power hypothesis of Shepherd
(1982)). Alternatively, if higher market power of foreign banks results from their superior performance and acquisition of less efficient banks, this should be welcomed
by the supervisors (the efficient-structure hypothesis of Demsetz (1973)).
We believe that our paper is the first one that rigorously treats the effects of selection bias during foreign bank acquisitions on the post-acquisition performance. Our
empirical strategy yields a number of interesting results. We show that foreign investors did not acquire banks at random, but chose institutions with large market
power. Moreover, the acquired banks were often in poor financial condition, as measured by the return on assets (ROA). Controlling for this selection bias, we find a
positive impact of foreign bank ownership on acquired banks’ performance, as well
as on their market power. We show that during three years after the takeover, banks
have become more profitable due to cost minimization and better risk management.
They have additionally gained market share, because they passed their lower cost of
funds to borrowers in terms of lower lending rates. Our methodology offers us also
a unique possibility to track the dynamics of banks’ post-acquisition performance.
We show that while the changes in profitability appear one year after the acquisition,
market share increases only one period later. In total, the results of our analysis lead
us to believe that previous studies failed to pick up these improvements in banks’
performance because they assumed that acquisitions were done randomly.
The paper is structured as follows. In Section 2. we shortly review the relevant
literature. Section 3. describes methodology and Section 4. presents our dataset
and Section 5. computes descriptive statistics. Section 6. analyzes the results of the
10
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
propensity score matching model and Section 7. includes findings about the effect of
foreign ownership using difference-in-difference technique. In Section 8. we report
additional robustness checks and Section 9. concludes.
2.
R ELATED LITERATURE
In order to analyze the effects of cross-border bank mergers, the most accepted
method in the empirical literature is to introduce a dummy variable that takes the
value of one for a bank after it has been acquired by a foreign institution and 0 otherwise. However, such an approach mostly fails to pick up any significant changes in
the post-acquisition performance of banks. There are few plausible explanations for
this. First of all, foreign investors might have targeted domestic banks with certain
characteristics, like higher profits or bigger market share. Second, banks that chose
to enter via takeovers were usually facing administrative entry barriers which often
loosened in the wake of the crises. Thus, they operated in less favorable conditions
during their first few years of existence. Finally, earlier studies do not look at the
possible transition period that follows the takeover. It could take a few years for a
bank to be reformed and initially we might even observe, for example, an increase
of costs as the bank is spending more on training of its employees and investing in
modern technology.
One of the earliest attempts to address the issue of selection bias is done in the work
of Peek, Rosengren & Kasirye (1999) that focuses on the period around the time of
ownership changes in the US. They try to determine whether poor performance of
foreign banks is the result of changes in business strategy or the preexisting characteristics of target banks. Their findings indicate that target banks of foreign acquirers
exhibit lower profitability prior to the acquisition, during the transition period, and in
the long run after the change of ownership.
Berger, Miller, Petersen, Rajan & Stein (2005) differentiate explicitly between static,
selection and dynamic effect of foreign ownership using data on Argentinean banking
sector. They investigate the impact of these effects on five variables: profit efficiency
rank, ROE, cost efficiency rank, cost-to-asset ratio, and the ratio of non-performing
loans. Their data suggests that foreign ownership is associated with lower profit
efficiency than domestic ownership (static effect), that acquired banks did not differ
significantly from the banks that have remained domestic except for slightly higher
costs (selection effect), and that there was little improvement in the performance of
banks after the acquisition (dynamic effect).
Lanine & Vander Vennet (2007) show that foreign banks acquired larger banks in the
Central and Eastern European countries. However, they do not account for this endogeneity problem and estimate the impact of foreign bank acquisition using regression
11
CEPII, Working Paper No 2008 – 16
techniques by introducing a dummy variable to capture foreign ownership. They find
that banks acquired by foreign investors benefit in terms of higher market share in the
post acquisition period, but the impact on efficiency and profitability is negligent.
By focusing on the trade-off between performance and market power, our paper is
also related to the extensive literature that analyzes the relationship between market
structure and performance of banks. According to the structure-conduct-performance
hypothesis, higher market concentration leads to imperfect competition. This allows
banks to set prices that are less favorable to consumers and results in higher bank
profits (see Berger, Demsetz & Strahan (1999), for a survey). A similar hypothesis
of relative market power asserts that only firms with large market power and welldifferentiated products are able to exercise market power in pricing these products
and earn abnormal profits. Additionally, it is hypothesized that managers of large
firms could make less effort to maximize efficiency - the so called “quiet life” effect
(Berger & Hannan (1998)). An alternative explanation of the positive relationship
between high concentration and profitability is offered by Demsetz (1973). She formulates the efficient-structure hypothesis, which suggests that more efficient banks,
which are also more profitable, gain large market shares, which may result in high
levels of market concentration.4
We contribute to the above literature by estimating the impact of foreign ownership on
performance and market power of acquired institutions by using a new methodology,
which allows us to overcome the selection bias. The methodology is described in
detail in the following section.
3.
M ETHODOLOGY
The aim of our analysis is to estimate the causal effect of foreign ownership on bank
performance. To do this we use a method that is based on matched sampling (Heckman, Ichimura & Todd (1997), Heckman, Ichimura & Todd (1998)). This approach
is mainly used in labor economics, but has also been successfully incorporated into
studies that analyze causality between exports and productivity of firms (De Loecker
(2007)), as well as impact of foreign direct investment on performance of firms
(Arnold & Smarzynska-Javorcik (2007)). More recently, this method was used in the
banking analysis, but it was applied to firm level data (Giannetti & Ongena (2008)).
We believe that we are the first to apply this method to bank level data and analysis
4
Berger (1995) attempts to distinguish between the structure-conduct-performance, relative-marketpower and efficient-structure hypotheses and, even thought he finds that the superior X-efficiency is
associated with higher profits, he does not find proof that this leads to higher concentration of the
market. His results provide support for the relative-market-power hypothesis but run contrary to the
structure-conduct-performance paradigm.
12
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
of post-acquisition bank performance.
Our empirical estimation proceeds as follows. As a first step, we use propensity score
method and estimate a probability that a domestic bank is taken over in a given year
by a foreign bank. This probability is subsequently used to match each takeover bank
to a bank that remained in domestic hands. Since we match each foreign bank to a
domestic bank with a similar set of observable characteristics in the year preceding
the takeover, we limit, if not eliminate, the selection bias. Next, to asses the impact
of foreign acquisitions, we use difference-in-difference approach and compare the
performance of takeover banks with the matched domestic banks. We concentrate on
the changes in performance that take place within the same bank after the takeover
in comparison to the matched bank. While this limits the number of observations
that we are able to use in our analysis, it allows us to draw conclusions regarding
the causal effect of foreign acquisition, as well as to account for all time-persistent
non-random elements of the acquisition decision.
Here we present a more formal outline of the chosen procedure. First, we define a
treatment indicator Tit that equals one if bank i is taken over by a foreign investor
in year t and zero otherwise. The potential outcomes are then defined as Yi (Ti ) for
each bank i, where i=1, . . . , N and N denotes the total population. Hence, the causal
effect of foreign acquisition on bank performance (τAT T , the Average Treatment of
the Treated, ATT) can be defined as:
τAT T = E(τ |T = 1) = E[Y (1) − Y (0)|T = 1]
(1)
= E[Y (1)|T = 1] − E[Y (0)|T = 1]
which is the difference between the expected performance of a bank that was acquired
by a foreign investor (E[Y (1)|T = 1]) and the analogous outcome of the same bank
had it not been acquired (E[Y (0)|T = 1]). The latter outcome - (E[Y (0)|T = 1])
- is a counterfactual that is not observed, and therefore one has to select a proper
substitute for it in order to estimate ATT. Using the mean outcome of banks that
have remained domestic (E[Y (0)|T = 0]) is not a good choice, because it is most
likely that factors which determine the acquisition decision also determine the postacquisition performance. One method to resolve this selection problem is to construct
a counterfactual using propensity score matching. This technique relies on estimating the probability of a bank being acquired by foreign investors given an observed
set of bank characteristics X (Rosenbaum & Rubin (1983a), Rosenbaum & Rubin
(1983b), and Rosenbaum & Rubin (1984)), and then matching taken-over banks with
domestic banks with values of probabilities that are close to the taken-over banks.
Naturally, the validity of this technique relies on two assumptions: 1) that takeover
decision is based on the set of observables included in the estimation, 2) that banks
with similar probabilities would evolve in a similar manner. Hence, the performance
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CEPII, Working Paper No 2008 – 16
of an acquired bank can be written as:
E[Y (1) − Y (0)|T = 1] = E[Y (1)|T = 1, X] − E[Y (0)|T = 0, X]
(2)
− E[Y (0)|T = 1, X] − E[Y (0)|T = 0, X]
The second term in Equation (2) denotes the difference between the performance
of an acquired bank had it not been acquired, and a domestic bank. This selection
bias is assumed to be zero, conditional on the set of observable characteristics that
determine the takeover decision X. In this case, the remaining difference between
acquired banks and matched domestic banks represents the causal effect of foreign
ownership, and can be estimated using the available data.
To perform the propensity score matching technique, we first estimate the logit regression where we model the probability of being acquired by foreign investor on the
basis of bank specific and country specific characteristics:
1 if βXit−1 + εit > 0;
(3)
Tit =
0 otherwise.
where Tit is the treatment indicator defined above, Xit−1 is a vector of factors that
determine the probability of a bank of being acquired by foreign investors. It is
important to stress that we want to capture the probability of being acquired, and not
the probability of being foreign-owned. This is the reason why Tit is equal to 1 only
in the year of acquisition, and not for all years when bank is in foreign ownership.
Consequently, in the logit regression observations after the year of acquisition are
dropped. Greenfield banks, as well as banks that were foreign throughout our sample
are excluded since they are foreign-owned the whole time, and we cannot investigate
the probability of them being acquired.
Based on Equation (3) we assign the propensity score, i.e. the probability of being
acquired, to each bank. At this stage it is important to ensure that the balancing hypothesis is satisfied. The latter states that for a given propensity score, exposure to
treatment is random, and therefore treated and control banks should be on average
observationally identical. In practice, we split the sample into equally spaced intervals in which the average propensity score of treated and control banks does not
differ and, within each interval, we test whether the mean of every variable of X is
the same in the treated and control groups. In this way we match on the probability
to be acquired by foreign investors controlling for characteristics captured by X.
Now we can match each foreign bank with a domestic bank that has the closest
propensity score, but has never been acquired. There are several algorithms to do
so, and we rely on the most commonly used in the literature, namely Nearest Neighbor Matching. We match each acquired bank with a bank that remained domestic and
14
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
is the closest in terms of propensity score value to the acquired bank.5
Finally, when we have matched foreign banks with similar domestic banks, we are
able to use difference-in-difference approach. That means that we calculate the ATT
presented in Equation (2) and subtract from it the difference in performance between
acquired bank and a matched bank one year before the takeover:
AT T0+t
N
1 X
f oreign
control
=
Banki,0+t
− Banki,0+t
N
−
1
N
i=1
N X
f oreign
control
Banki,−1
− Banki,−1
(4)
i=1
where Bank f oreign and Bank control is a bank characteristic of interest for the foreign and control bank, respectively. The year of acquisition is defined as year 0. Since
the impact of foreign acquisition on the acquired bank probably does not manifest immediately, we additionally calculate AT T for 1, 2, and 3 years after the acquisition.
A more common procedure to estimate ATT is just to use first half of the formula (4)
which computes the difference between foreign banks and the control group. This
would be correct if we believed that the selection was based only on observable bank
characteristics. Combining matching with difference-in-difference approach allows
some scope for unobserved determinants as long as they can be represented by separable individual- and/or time-specific components of the error term. In this case, we
look at the before-after evolution instead of levels, and if there were some unobservable characteristic that led to banks being acquired, we can control for their evolution
as well (Blundell & Costa Dias (2000)).
The AT T presented in formula (4) shows the effect of takeover on bank performance
after 1, 2, or 3 years per year. In order to analyze whether these effects persist over
time, we additionally compute cumulative AT T , which shows the effect of takeover
from zero up to the 1st, 2nd or 3rd year after takeover:
"
J
N
X
1 X
f oreign
control
AT Tc,0+t =
Banki,0+t
− Banki,0+t
(5)
N
t=1
i=1
#
N X
1
f oreign
control
−
Banki,−1
− Banki,−1
N
i=1
where t stands for the period and J= 1, 2, 3.
5
One can argue that if the distance between a foreign bank and its matched counterpart is very large,
this matching is not useful. To address this issue, we tried to limit the search for the nearest neighbor to
25, 50, 100 closest observations, but the final results were not influenced by this exercise.
15
CEPII, Working Paper No 2008 – 16
Testing the statistical significance of AT T is not straightforward because the estimated variance of the treatment effect should also include variance arising due to the
estimation of the propensity score. To circumvent this problem, we use bootstrapped
standard errors. We set the number of bootstrap replications to 1000.
The main disadvantage of our chosen methodology is the need of a large dataset that
has bank information for at least two consecutive years. This should apply to acquired
banks, as well as to domestic banks which are matched with them. We have identified 73 foreign acquisitions that satisfy these criteria, but the number of analyzed
transactions decreases to 54 when we analyze the impact after three years of foreign ownership.6 The lack of large database also prevents us from constructing more
data demanding measures of performance, such as X-efficiency or profit-efficiency.
Therefore, we focus on more simple accounting measures, such as ROA and market
share.
4.
D ESCRIPTION OF THE DATA
All bank-specific information used in this study comes from Bureau Van Dijk’s BankScope database. We extract from it information on banks operating in 11 countries
in Central and Eastern Europe (Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, and Slovenia) between 1993 and
2005. As a result, our panel contains balance sheet and income statement figures on
352 commercial and saving banks in CEECs. We exclude investment banks, microfinance banks and development banks. For all these banks we use unconsolidated
statements whenever possible, relying on consolidated statements otherwise. The
data on macroeconomic variables is taken from the International Financial Statistics
of the IMF, and the indicators of the competition in CEECs from the EBRD Transition reports. The definitions of variables and all data sources are given in Table
1.
Appropriate information on bank ownership is crucial to our analysis. As the BankScope database lacks historical ownership data, for the years 1994-2001 we use information kindly provided by De Haas & Van Lelyveld (2006). For the four remaining
years we determine the ownership changes ourselves, on the basis of banks’ official
publications and central bank reports. We categorize a bank as foreign in a given year
if at least 51% of its capital was owned by foreign investors. Due to the on-going pri6
We have also tried to delete control banks that do not have enough consecutive observations before performing the matching, and then match foreign bank with a domestic bank that had the nearest
propensity score (and all the consecutive observations). This gives us a higher number of observations,
but this also leads to the bias, since we delete worse performing banks, which are more likely to provide
worse data. Our final results were not influenced by this.
16
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
vatization process in CEECs there is a need to account for the state bank ownership.
Therefore, we construct a dummy State-owned based on the information that was
made available to us by local banking supervisory authorities.
Table 1: Variable definition and sources
Symbol
ROA
Lending rate
GDP
Description
Return on assets, calculated as ratio of profits after taxes
to total assets
Net interest margin, calculated as ratio of net interest income to total assets
Bank capitalization, calculated as a ratio of bank equity
capital to total assets
Ratio of personnel and other operating expenses to total
assets
Dummy taking the value of 1 for countries experiencing
a banking crisis
Ratio of interest income to total assets
Ratio of interest expense to total assets
Loan loss provisions, calculated as ratio of loan loss provisions to interest income
Bank size, calculated as a logarithm of bank assets
Share of loans of a bank in the total loans of banking
sector in host country
Average bank lending rate adjusted for inflation
Real rate of growth of GDP
GDP_PC
Logarithm of real GDP per capita
FDI
Ratio of FDI to GDP
Trade
Ratio of sum of exports and imports to GDP
State-owned
Dummy taking a value of 1 for banks where over 50% of
capital is owned by the state
EBRD index of competition reforms
NIM
CAP
Costs
Crisis
Interest income
Interest expense
LLP
Size
Market Share
EBRD
Source of data
BankScope
BankScope
BankScope
BankScope
Caprio & Klingebiel
(2003)
BankScope
BankScope
BankScope
BankScope
BankScope
BankScope
World Development
Indicators
World Development
Indicators
Lane & MilesiFerretti (2006)
World Development
Indicators
Own research
EBRD Transition
Reports
After combining the dataset, we aggregate the data for banks that merged in the
course of the period analyzed in our study. We do this to ensure that we capture the
effect of foreign ownership and not the effect of domestic mergers and acquisitions.
17
CEPII, Working Paper No 2008 – 16
5.
D ESCRIPTIVE STATISTICS AND EVIDENCE OF THE SELECTION BIAS
Table 2 presents descriptive statistics for the following bank characteristics: return on
assets (ROA), net interest margin (NIM), Capital, Costs, Interest Income, Interest Expenses, Size (measured as natural logarithm of total assets), Market Share, Loan Loss
Provisions (LLP). We present mean and standard deviation for the above variables for
banks that have remained domestic during the analyzed sample (Domestic), and for
banks that have been taken over (Takeover). It should be mentioned, that Takeover
represents the statistic for all observations available for a takeover bank, both before
and after the acquisition. Then we calculate the statistics separately for the period
before (Before) and after the takeover (After). The columns A, B, and C show the
results of t-statistic tests for the difference in means between takeover and domestic
banks (column A), takeover banks before, takeover banks after the takeover and domestic banks (column B), and between takeover bank before and after the takeover
(column C).
Our descriptive statistics show that banks that became targets of foreign acquisitions
significantly differed from other domestic banks. First, acquisition targets held almost 25 percent less equity in relation to total assets that domestic banks, and incurred total costs lower by almost 23 percent. The most striking difference can be
seen in the comparison of market shares, however. Acquired banks controlled on
average over twice as high a market share than banks that remained domestic during
the analyzed period. If we assume that large banks as a rule have lower costs due to
economies of scale and can afford to hold less capital, we can conclude that foreign
investors primarily picked large banks as their targets in order to gain market power.
Next, to see whether the performance of target banks changed after the acquisition
we compare the performance of banks before and after takeover. The results of t-tests
are presented in column C. This basic statistics suggest that foreign owners were not
able to maintain high market share of acquired institutions: market share dropped by
almost 26 percent with respect to pre-takeover levels. At the same time, the average
size of takeover bank increased by 3.5 percent. These seemingly contradictory results can be explained by the increasing presence of greenfield banks and the possible
change in strategies of domestic banks. While new owners of acquired banks, compete for clients with greenfield banks, they find themselves at a disadvantage because
they are burdened by inherited non-performing loans. In contrast, greenfield banks
start their operations from scratch and can grow faster by offering lower interest rates
to attract clients. Moreover, better macroeconomic conditions and improving credit
assessment skills of employees might have encouraged remaining domestic banks to
start granting more loans. As a result, while foreign banks increased in size, they
lost substantial part of their market share, because other types of banks grew even
18
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
faster. In order to counteract this loss, banks seemed to have decreased their interest
margins, as manifested in NIM that declined by 16 percent.
Table 2: Descriptive statistics
ROA
NIM
CAP
Costs
Interest income
Interest expense
Market share
Size
LLP
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Domestic
Takeover
Before
After
Mean
0.416
0.544
0.378
0.691
0.416
0.544
0.378
0.691
15.208
12.735
12.186
13.221
5.791
4.312
4.470
4.169
10.464
9.952
12.505
8.074
5.835
5.725
8.018
4.039
4.349
9.037
10.511
7.732
12.116
13.373
13.130
13.583
14.893
13.175
15.015
11.525
S.Dev.
7.188
4.595
5.937
2.932
7.188
4.595
5.937
2.932
13.535
12.081
13.756
10.363
14.922
7.653
8.658
6.620
7.293
6.184
7.612
3.936
5.883
5.661
7.399
2.950
9.018
11.943
13.439
10.278
1.651
1.754
1.748
1.732
56.235
87.636
28.137
117.769
A
B
C
***
***
***
***
***
***
***
*
**
***
***
***
***
***
***
***
***
***
***
***
***
***
***
∗∗∗ ∗∗
, , and ∗ correspond to 1%, 5% and 10% significance levels that the following differences
in means are different from zero: in column A - between takeover and domestic banks, in column
B - between takeover banks before takeover, takeover banks after takeover, and domestic banks
respectively, in column C - between takeover banks before and after takeover.
19
CEPII, Working Paper No 2008 – 16
2
9
8
1,5
7
1
6
0,5
5
4
0
3
-4
-3
-2
-1
0
1
2
3
4
-0,5
2
-1
1
0
-1,5
-4
Takeover
Greenfield
Domestic
-3
-2
-1
Takeover
(a) ROA
0
1
Greenfield
2
3
4
Domestic
(b) Market Share
Figure 1: Trajectories for ROA and Market Share for takeover, greenfield, and domestic banks
To better visualize the presence of the selection bias, we plot the evolution of ROA
and market share over time for takeover banks on Figure 1. We also plot the average
performance of greenfield banks. The period 0 refers to the date of acquisition for
takeover banks and the date of establishment for the greenfield banks. We compare
performance of these banks with the average performance of banks that have always
stayed in domestic ownership. We restrict our analysis only to three years around the
date of bank acquisition or establishment due to the data availability constraints. We
find that both profitability and market share of the acquired banks were decreasing
before acquisition and grew afterwards, which is in line with the evidence that many
banks were acquired in the wake of the crises or when they experienced financial
difficulties. It is interesting to note that the trajectory of ROA seems to be much
more dramatic than the one for the market share, even though the t-statistic fails
to show the difference in the pre- and post-acquisition performance. Hence, these
figures can be additionally interpreted as showing the importance of controlling for
the transition period after the takeover in order to understand the time requirements
of new investors to reform an acquired bank.
6.
P ROPENSITY SCORE MATCHING TO CONTROL FOR THE SELEC TION BIAS
In order to analyze the effect of takeover on the performance of banks operating in
CEECs, we next turn to the propensity score and DID methodology. To estimate
propensity scores, we rely on the logit regression (3), where the dependent variable
is equal to 1 for the year of acquisition and 0 otherwise. We select our conditioning
20
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
variables to control for factors that are expected to affect both the acquisition decision
and the performance after the acquisition, or proxy for the unobservables that play a
role in both dimensions. In our choice of model specification we rely on the literature
that analyzes the factors influencing entry decisions of foreign banks (Magri, Mori &
Rossi (2005); Berger & Udell (2004)).
First of all, we control for bank-specific characteristics to see whether foreign investors chose particular targets when they make acquisition decisions. In particular,
we investigate whether the entry decision was motivated by profitability and financial health concerns or rather by the market power of domestic banks. To this end, we
include bank profitability (measured by ROA), capitalization (CAP) and bank Size.7
In addition we control for state ownership of banks since public institutions are not
always motivated by profitability or efficiency concerns, but might exercise development functions, like extending loss making loans to subsidize “social projects”
(La Porta, Lopez-De-Silanes & Shleifer (2002)).
Second, we control for the “follower relationship hypothesis” which states that banks
follow their customers from home countries, being afraid of loosing them once they
have established relationships with banks operating in foreign countries (Grubel
(1977)). Hence, we include a ratio of foreign direct investment to GDP (FDI) to
control for the degree of economic integration among countries. We expect it to have
a positive effect on the probability of being acquired.
Third, we use a set of variables to investigate the role of local market profit opportunities in attracting foreign banks. Abundant evidence shows that foreign banks
succeeded to capitalize on their comparative advantages in relatively poor countries
with inefficient and uncompetitive banking sectors (Claessens, Demirgüç & Huizinga
(2001)). To control for this we include the log of host country GDP per capita
(GDPPC) and a real lending rate (Lending rate), which serve as proxies for banking sector efficiency. Bank efficiency is highly positively correlated with the level of
economic development (Buch, 2004) and high lending rates might signal inefficiency
of local financial intermediation, which promises more profits for foreign banks if
they take over domestic institution and cut costs.
Next, we incorporate the real GDP growth (GDP_GR) into the logit regression, with
which we hope to pick up the timing of takeovers. On the one hand, we can expect
that most takeovers took place when local economies were growing fast and were
more attractive. Alternatively, some countries allowed foreign bank entry only when
they did not succeed to reform the banking sector. As a result, foreign banks entered after crisis periods and during low growth. Finally, we include EBRD index
of competition reforms to control for the regulatory environment in which banks and
7
We experiment with this variable and use either bank Size or Market Share. The results are robust
to the inclusion of either of the two variables, hence we present only the results with Size
21
CEPII, Working Paper No 2008 – 16
firms operate. One could argue that foreign banks only enter banking sectors that
sufficiently protect property and creditor rights.
The results of the logit regressions are presented in Table 3. The descriptive power of
the model is relatively high when compared to similar models (Arnold & SmarzynskaJavorcik (2007); Lanine & Vander Vennet (2007)). Before turning to the analysis of
our results we should also note that the balancing hypothesis is satisfied. This means
that the mean of every explanatory variable has to be the same for the treated and
control group in every block.8 This ensures that observations with the same propensity score have the same distribution of observable characteristics independently of
the treatment status (takeover or no takeover). In other words, for a given propensity score, exposure to treatment is random and therefore treated and control units
should be on average observationally identical. The fact that balancing hypothesis is
satisfied indicates that we control for the selection bias.
Our model of propensity of being acquired by foreign investors shows that there is
an important selection bias when it comes to acquisition decisions. Foreign investors
were attracted by targets that were large and well capitalized. Interestingly, acquired
banks experienced on average lower profitability than their domestic peers, which reflected the situation when foreign investors were only allowed to acquire banks after
crises and/or when banks experienced financial difficulties. All these bank-specific
coefficients are economically relevant. An increase of one standard deviation in the
size of a bank increases the probability of it being acquired by 1.4 percentage points,
which is a significant amount taking into account that the average probability of a
bank being acquired in a given year amounts to 4.1 percent. Similarly, a decrease
of one standard deviation in ROA increases the probability of acquisition by 0.5 percentage points. Despite the belief that most foreign investors acquired banks during
the privatization process, being owned by the state decreased the probability of acquisition by 1.1 percentage points. In fact, with the exception of a few large banks in
each country, foreign banks mostly took over private institutions.
Among country characteristics, the important role was played by the ratio of foreign
direct investment to GDP, which is consistent with the “follower relationship hypothesis”. An increase in FDI by one standard deviation increases the probability of a
bank from the FDI-receiving country being acquired by 1.3 percentage points. To
illustrate, such an increase would correspond to Croatia increasing its volume of FDI
inflows in relation to GDP in 2004 to the level of Hungary in 1993. The high real
lending rate on the market showed its inefficiency, promised high future profits after
the restructuring of the target bank, and also had a positive impact on probability
of being acquired. One standard deviation increase in real interest rate raised the
8
We do not present the results because they are very long, but, of course, they are available upon
request.
22
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
probability of bank being acquired by 3 percentage points.
Table 3: Logit regression
ROA
CAP
State-owned
Size
EBRD
Lending rate
FDI
GDPPC
GDP_GR
Pseudo R2
Observations
Chi2
Prob. > Chi2
Coefficient
-0.028***
[0.0108]
0.0225**
[0.012]
-0.494*
[0.292]
0.312***
[0.104]
2.309***
[0.509]
0.082***
[0.029]
0.198***
[0.041]
-1.830***
[0.430]
-0.080**
[0.041]
Change -+1/2 std. dev.
-0.0051
0.0080
-0.0055
0.0137
0.0682
0.0300
0.0131
-0.0178
-0.0082
Marginal effect
-0.0007
[0.0003]
0.0006
[0.0003]
-0.0111
[0.0065]
0.0077
[0.0028]
0.0571
[0.0113]
0.0020
[0.0005]
0.0049
[0.0012]
-0.0453
[0.0115]
0.0020
[0.0009]
0.12
1388
59.66
0.00
The table lists coefficients and standard errors (in parentheses) in column 1, the impact of the
change of -+ standard deviation of the right-hand-side variable on the dependent variable (column 2), and marginal effects (column 3). All dependent variables are lagged by one year.
Regressions include seasonal dummies. Definitions of variables are provided in Table 2. ***,
**, and * correspond to 1%, 5% and 10% significance levels. EBRD index is not a continuous
variable, we present the effects of increase in the index by 1 unit.
It is interesting to see that even though foreign banks preferred countries with underdeveloped banking sector, they were more likely to enter markets with more competitive environment for firms, as measured by the EBRD index. For example, in
1995 domestic banks in Poland had 6.8 percentage points higher probability of being
acquired than banks in Lithuania. This can be interpreted as a sign that foreign banks
were more likely to enter countries with good prospects for profits from lending, but
with still uncompetitive financial markets. Furthermore, the fact that foreign banks
chose to enter when economies were still poor (as measured by GDP per capita)
and growing slowly (overall country GDP) is probably due to lower price of target
23
CEPII, Working Paper No 2008 – 16
banks. The negative impact of GDP growth is also consistent with the observation
that foreign bank entry was often allowed only in the wake of the crises when local
authorities experienced financial difficulties.
Our results are broadly in line with the existing literature that analyzes factors that
influence the decision of foreign banks to enter new markets. However, we should
note that in most of these papers the dependent variable is not constructed on a bank
level, but country level. Magri et al. (2005) measure the number of foreign banks by
country of origin as a share of the total number of banks operating in Italy. Berger &
Udell (2004) analyze the number of mergers between banks from different countries,
whereas Buch (2000) looks at the amount of foreign direct investment from Germany into banking sectors of different countries. Our results are directly comparable
to finding of Lanine & Vander Vennet (2007) who find that, among bank characteristics, the size is the most important bank characteristic that explains the acquisition
decisions of foreign investors in CEECs.
7.
R ESULTS
FROM THE DIFFERENCE - IN - DIFFERENCE ANALYSIS ON
THE MATCHED SAMPLE
Once we have computed propensity scores based on the model discussed in Section
6., we can proceed with our difference-in-difference analysis. As it was already mentioned in Section 3., we compute ATT following the formula (4), and the cumulative
ATT using the formula (5). We additionally impose an important assumption and
match foreign banks with domestic banks that have the closest propensity score but
only in the same year. We rely on such sub-population matching, because there were
massive economic reforms throughout the analyzed period in CEECs which have
changed the performance of many banks. Therefore, if we do not control for time,
we risk matching the performance of a foreign bank in the post reform period with the
performance of a domestic bank prior to these changes. Even though, we control for
many macroeconomic and structural changes in our logit regressions, the differences
could still remain and the safest way to avoid mistakes is to match banks separately
within each year. Moreover, we only match banks that fall on common support. The
results are presented in Tables 4 to 9.
In Table 4, we present our results for the two main variables of interest; namely ROA
and market share. To capture the transition period, we present ATT for the acquisition
year and one, two and three years after the takeover (panel A), and the cumulative
results after one, two and three years (panel B).
24
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
Table 4: Results of the matching procedure for ROA and Market Share
ROA
Market share
No. of observations
0.094
[0.834]
2.556***
[1.011]
2.084***
[1.001]
1.714*
[0.968]
0.304
[0.577]
0.819
[0.688]
1.843**
[0.884]
2.288**
[0.978]
73
2.775*
[1.579]
4.968**
[2.444]
7.795**
[3.570]
1.272
[1.286]
3.404*
[2.009]
5.686*
[3.506]
69
Panel A: Annual effects
Acquisition year
One year later
Two years later
Three years later
69
61
54
Panel B: Cumulative results
One year later
Two yearS later
Three years later
61
54
The table lists coefficients and bootstrapped standard errors (in parentheses) of the Difference in
Difference methodology for estimating the impact of foreign acquisitions on ROA and Market share
of takeover banks. Annual effects are presented in Panel A, and cumulative effects in Panel B.
Definitions of variables are provided in Table 2. ***, **, and * correspond to 1%, 5% and 10%
significance levels.
Our findings show that foreign acquisition has no impact on the bank in the year
of the acquisition, but starting from the first year, there is a sustained increase in
profits relative to domestic banks that are in the control group. Two years after the
acquisition, market share of the acquired banks starts to increase as well. We find
that after three years foreign investors succeed to increase profitability of an average
acquired bank by 1.7 percentage points and to gain additionally 2.3 percentage points
of the market share. This is an economically significant result, especially when we
take into account that average ROA for banks that remained in domestic hands was
0.38 percent and average market share for the same institutions was 10.25 percent.
While the result for market share might seem contradictory to the descriptive statistics
(as can be seen in Table 2, market share of takeover banks decreases with respect
to the pre-takeover value), it is important to remember that here we compare the
takeover banks to the matched domestic institutions. Our results are robust if we
look at the cumulative effects (panel B). The increases in both ROA and market share
are not a one-time phenomenon and persist over time.
25
CEPII, Working Paper No 2008 – 16
As we do not observe a very high number of mergers in CEECs, we decided to use all
possible observations for every year after the takeover. This implies, however, that we
do not have the same number of observations each year: the number of observations
declines in the post-acquisition period since some banks do not have all the data
for consecutive years. In order to make sure that our results are not driven by a
sample bias, we perform the same exercise restricting the number of banks to those on
which we have data for two consecutive years after the acquisition. Next, we restrict
the sample to banks for which we have observations for three consecutive years.
The results on the same sample are presented in Table 5 and support our previous
findings. Bank profits start rising one year after the acquisition, while market share
starts increasing in year 2. Actually, with the restricted samples the results for ROA
are even higher than with all observations included, while the results for market share
remain virtually the same.
Table 5: Results of the matching procedure for ROA and Market Share - same
sample size
Acquisition year
One year later
Two years later
ROA
0.059
[0.907]
2.944***
[1.135]
2.084***
[1.001]
Market share
0.589
[0.649]
0.976
[0.739]
1.843**
[0.884]
ROA
0.538
[0.922]
3.189***
[1.259]
2.354**
[1.141]
1.714*
[0.968]
Market share
0.552
[0.750]
1.006
[0.865]
1.840*
[1.022]
2.288**
[0.978]
61
61
54
54
Three years later
No. of observations
The table lists coefficients and bootstrapped standard errors (in parentheses) of the Difference in
Difference methodology for estimating the impact of foreign acquisitions on ROA and Market share
of takeover banks. First two columns present the results for the same sample up to two years after
the takeover, columns 3 and 4 for three years after the takeover. Definitions of variables are provided
in Table 2. ***, **, and * correspond to 1%, 5% and 10% significance levels.
Looking at the results in Tables 4 and 5, we do not find any evidence that foreign
banks attempt to increase their market share at the expense of lower profits. It rather
seems that good performance of foreign banks makes them more attractive to clients,
which in turn increases their market share. This is in line with “efficiency ” hypothesis and, therefore the increased concentration of the market reflects a more competitive banking industry. This result is contrary to the evidence found for developed
26
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
markets such as the US and Australia by DeYoung & Nolle (1996) and Williams
(1998a), Williams (1998b), Williams (2003). They argue that foreign banks did not
succeed in developing a relationship with retail customers and therefore had to rely
on expensive purchased funds, which decreased their profits. The situation in transition countries is different because by acquiring existing domestic institutions foreign
banks already inherit the customer network and can benefit from it. Furthermore,
foreign banks that enter transition countries have an advantage of better access to the
international capital market which provide cheaper funds than those raised through
deposits.
More generally, our results are in line with Demirgüç-Kunt, Laeven & Levine (2004)
who find that restrictions on bank entry and other regulatory obstacles that inhibit
the freedom of bankers to conduct their business increase costs of intermediation.
We complement this finding by showing that eliminating restrictions on foreign bank
ownership boosts performance of acquired banks.
Our findings also contribute to the discussion on fast loan growth in CEECs (e.g.
Cottarelli, Dell’Ariccia & Vladkova-Hollar (2005), since we show that one of the
driving forces behind this trend is foreign bank ownership, notwithstanding the mode
of entry. These are very important results, since earlier studies show that market
shares of greenfield banks grow faster than those of domestic banks, but fail to pick
up faster growth of takeover banks (De Haas & Van Lelyveld (2006)). The reason that
we have different results lies in our careful treatment of the selection bias. We show
in Section 6. that foreign investors choose to acquire large institutions in order to gain
market power, and naturally such institutions cannot grow as fast as new small banks.
However, traditional regression techniques do not allow to take this fact into account,
even if the bank size is controlled for. Therefore, our careful matching technique
helps to overcome the selection bias and produces unbiased results.
To further verify the robustness of our results, and to get more insight on particular
sources of higher profitability of foreign banks after the takeover, we compute the impact of foreign acquisitions on the following variables that capture difference facets
of bank performance: net interest margin, capitalization, costs, interest income, interest expenses, size, and loan loss provisions. We first present results in Table 6 for all
available banks, and then in Table 7 we show results on the same samples restricted to
banks that have continuous information for two and three years after the acquisition.
We note that the results are robust notwithstanding the sample.
27
28
-0.480
[0.371]
-0.066
[0.628]
-0.461
[1.045]
0.155
[1.656]
-0.480
[0.371]
0.226
[0.367]
-0.016
[0.422]
0.368
[0.502]
NIM
2.755*
[1.557]
6.154*
[3.232]
9.177*
[5.163]
16.290**
[6.640]
2.755*
[1.557]
2.878
[1.816]
1.711
[2.009]
3.540*
[1.992]
CAP
-3.195
[3.200]
-4.091*
[2.222]
-5.461**
[2.341]
-7.660***
[2.714]
-3.195
[3.200]
-0.558
[2.109]
-2.395***
[0.948]
-1.578***
[0.539]
Costs
-0.953
[0.705]
-1.954
[1.250]
-3.818*
[2.221]
-5.530*
[3.336]
-0.953
[0.705]
-0.697
[0.705]
-1.212
[0.910]
-0.899
[1.072]
Int. income
-0.473
[0.562]
-1.888*
[0.985]
-3.357*
[1.786]
-5.684**
[2.592]
-0.473
[0.562]
-0.923*
[0.561]
-1.196*
[0.719]
-1.268*
[0.775]
Int. expense
0.052
[0.816]
0.236*
[0.134]
0.572**
[0.236]
0.944***
[0.357]
0.052
[0.816]
0.161**
[0.076]
0.322***
[0.097]
0.348***
[0.114]
Size
22.790
[33.468]
12.737
[33.604]
4.729
[36.479]
-42.166**
[16.600]
22.790
[33.468]
-16.014***
[4.763]
-13.806***
[4.972]
-13.782**
[6.828]
LLP
54
61
69
73
54
61
69
73
No. of obs.
The table lists coefficients and bootstrapped standard errors (in parentheses) of the Difference in Difference methodology for estimating the
impact of foreign acquisitions on NIM, CAP, Costs, Interest Income, Interest Expense, Size, and LLP. Annual effects are presented in Panel A,
and cumulative effects in Panel B. Definitions of variables are provided in Table 2. ***, **, and * correspond to 1%, 5% and 10% significance
levels.
Three years later
Two years later
One year later
Acquisition year
Panel B: Cumulative effects
Three years later
Two years later
One year later
Acquisition year
Panel A: Annual effects
Table 6: Results of the matching procedure - decomposition of ROA and Size
CEPII, Working Paper No 2008 – 16
29
4.174***
[1.588]
5.326***
[1.867]
3.250
[2.118]
3.540*
[1.992]
61
3.422**
[1.716]
4.045**
[1.942]
1.711
[2.009]
CAP
-0.641
[0.526]
-3.018**
[1.561]
-2.424**
[1.058]
-1.578***
[0.539]
61
-0.346
[0.633]
-2.721*
[1.505]
-2.395***
[0.948]
Costs
-1.709**
[0.739]
-1.506*
[0.843]
-1.415
[1.019]
-0.899
[1.072]
61
-1.382**
[0.683]
-1.224*
[0.749]
-1.212
[0.910]
Int. income
-1.377**
[0.559]
-1.507**
[0.651]
-1.532**
[0.768]
-1.268*
[0.775]
61
-1.045**
[0.543]
-1.117*
[0.617]
-1.196
[0.719]*
Int. expense
0.089
[0.061]
0.186**
[0.089]
0.321***
[0.111]
0.348***
[0.114]
61
0.077
[0.066]
0.173**
[0.084]
0.322***
[0.097]
Size
-4.305
[4.402]
-13.010***
[4.697]
-11.069**
[4.632]
-13.782**
[6.828]
61
35.812
[40.685]
-17.278***
[5.187]
-13.806***
[4.972]
LLP
The table lists coefficients and bootstrapped standard errors (in parentheses) of the Difference in Difference methodology for estimating
the impact of foreign acquisitions on NIM, CAP, Costs, Interest Income, Interest Expense, Size, and LLP with a sample restricted to
two years after the takeover (panel A) and three years after the takeover (panel B). Definitions of variables are provided in Table 2. ***,
**, and * correspond to 1%, 5% and 10% significance levels.
Three years later
Two years later
One year later
Acquisition year
Sample restricted to 3 years
-0.332
[0.346]
0.002
[0.423]
0.117
[0.238]
0.368
[0.502]
61
No. of obs.
Two years later
One year later
-0.338
[0.318]
-0.108
[0.369]
-0.016
[0.422]
NIM
Acquisition year
Sample restricted to 2 years
Table 7: Results of the matching procedure - sample restricted to two and three
years after takeover
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
CEPII, Working Paper No 2008 – 16
We find a sign of recapitalization of acquired banks by foreign investors in the year of
takeover. In the following two years, the capitalization of foreign banks remains the
same as that of domestic banks, but the cumulative results are still significant. This is
consistent with the evidence that foreign banks were often only allowed to take over
banks which were in the need of recapitalization and restructuring.
Bank recapitalization is the only significant change that the acquired banks undergo in
the year of the acquisition. Other changes need more time. The streamlining of costs
is only possible two years after the acquisition, when the costs drop by 2.4 percentage
points. To see this number in perspective, it is informative to note that average costs
of banks that remained in domestic hands are 5.8 percent, indicating over 40 percent
drop. This two-year delay can be explained by the presence of agreements that foreign banks had to sign while acquiring a domestic institution, and which prevented
them from firing unnecessary personnel or closing superfluous branches directly after
the acquisition. Alternative explanation for this finding can be based on the results of
the theoretical model developed by Detragiache, Tressel & Gupta (2008). They show
that after the takeover, bank costs can increase because new owners start monitoring
the customers. If, in the same time, banks reduce redundant personnel expenses, total
costs can stay constant, or start falling only some time after the takeover.
Loan loss provisions of acquired banks start decreasing already one year after the
takeover. However, the cumulative effect of lower loan loss provisions appears to be
significant only after three years due to a sharp increase in loan loss provisions in the
year of the acquisition (which does not turn out to be significant due to high standard
errors). This result most likely indicates the reclassification of loans by new owners,
who apply tighter classification rules for non-performing loans. If this is the case, the
magnitude of our findings that foreign banks have less loan loss provisions is even
understated.
Lower loan loss provisions are likely to reflect improved risk management techniques
which allow banks to better screen their potential borrowers and thus lower nonperforming loans. However, foreign banks are also considered to have comparative
advantages at processing hard information, while domestic banks are better at handling soft information.9 Therefore, foreign banks might increase their lending to
large transparent companies, at the expanse of small entrepreneurs (Dell’Ariccia &
Marquez (2004). Degryse, Havrylchhyk, Jurzyk & Kozak (2008) show that foreign
9
Hard and soft information differ with respect to the degree of transferability. Thus, hard information
on the other hand refers to credible and publicly verifiable data, such as a firms’ balance sheets, credit
history, collateral and guarantees. On the other hand, soft information cannot be verified by a third
person and is gained a result of the relationship between a bank and a borrower. For example, through
repeated interviews with an owner of a young firm, a bank manager might be convinced that the firm’s
owner is a smart, honest and hard working entrepreneur with a high probability of success. However,
this soft information cannot be transferred to other potential lenders (Petersen, 2004).
30
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
banks that enter via establishment of greenfield operations lend particularly a lot to
large private companies and very little to entrepreneurs. The portfolios of foreign
banks that entered the market via takeovers of domestic institutions are more similar to domestic banks, but they also tend to lend less to small enterprises. These
changes in portfolio composition can also affect costs, since lending that is based on
soft information is very labor-intensive. Unfortunately, the BankScope data does not
provide portfolio information which could help us to answer this question, and more
research is needed to address this issue.
Higher profitability of foreign banks does not stem from higher interest margin,
which turns out to be insignificant in our calculations. This is surprising, since one
of the recognized advantages of foreign ownership is banks’ improved access to the
international capital markets either directly or via their parent banks, which should
significantly lower their costs of funding.10 However, if this is passed on to borrowers
in terms of lower lending rates in order to increase banks’ market share, we would
observe no final impact on NIM. To test this, we compute the impact of foreign acquisition separately on interest income and interest expenses of banks. We find a
negative influence on both variables, but it is only statistically significant in the case
of interest expenses. However, the cumulative results turn out to be significant for
both variables. Therefore, we can argue that borrowers directly benefit from lower
cost of funding, and this is also the reason why NIM remains stable in the wake of
banks’ acquisitions.
8.
A DDITIONAL ROBUSTNESS CHECKS
We have conducted a number of sensitivity analyses, many of which have been already mentioned before. Here we perform some additional robustness checks by
constructing new control groups based on new propensity scores which control for
additional characteristics that might influence the probability of being acquired and
the post-acquisition performance.
We have mentioned before that foreign banks were often allowed to take over domestic banks only in the wake of the crises and/or if target banks experienced financial
difficulties. We controlled for this by including different bank characteristics, and indeed we saw that less profitable banks were more likely to be acquired. However, in
the baseline model we did not include other measures that might capture this negative
selection bias because they were not significant and we thought it was less appropriate to include non-significant explanatory variables into model which was used for
10
Our experience suggests that foreign banks in CEECs have very high share of foreign interbank
liabilities, which mostly come from their parent banks. For comparison, domestic banks have virtually
zero foreign interbank liabilities.
31
CEPII, Working Paper No 2008 – 16
prediction. However, in order to test the robustness of our results, we augment our
baseline logit model with the lagged value of LLP and compute ATT using this new
control group. Alternatively, we augment our baseline model with the crisis dummy,
which takes the value of 1 during the years when the crisis hits a country in CEE. The
timing of the crisis it taken from the World Bank database “Episodes of Systemic and
Borderline Financial Crises” compiled by Caprio & Klingebiel (2003).
The results of the two exercises are presented in Table 8, in panels A and B respectively. It is important to point out that neither the lagged value of LLP nor the crisis
dummy are significant in the logit regressions. The results for ROA are robust for
the first and second year after the takeover, albeit somewhat smaller in magnitude
than in our base model. In the third year, the effect remains positive, although it is
not significant anymore. The results for market share remain significant, however
their magnitude also decreases, especially in the specification with the lagged value
of LLP.
Table 8: Results of the matching procedure controlling for LLP and crises
ROA
Market share
No. of obs.
0.053
[0.817]
2.010**
[1.005]
2.026*
[1.079]
1.474
[0.984]
0.068
[0.428]
0.400
[0.451]
0.988**
[0.476]
1.156*
[0.480]
73
-0.316
[0.750]
2.491**
[1.044]
2.020*
[1.172]
0.742
[1.081]
0.284
[0.433]
1.313*
[0.702]
1.978**
[0.930]
1.519**
[0.656]
73
Sample matched on lagged LLP
Acquisition year
One year later
Two years later
Three years later
69
61
54
Sample matched on occurrence of crisis
Acquisition year
One year later
Two years later
Three years later
65
56
49
The table lists coefficients and bootstrapped standard errors (in parentheses) of the Difference in Difference methodology for estimating the impact of foreign acquisitions on ROA and Market Share. Panel A
presents the results of DID when the initial matching was performed with a lagged LLP variable added
in the logit model, Panel B - with the lagged crisis dummy added to the logit model. Neither the LLP
not the crisis dummy were significant in the logit regressions. Definitions of variables are provided in
Table 2. ***, **, and * correspond to 1%, 5% and 10% significance levels.
32
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
The presence of foreign banks in a country has a profound impact on the competition
in the market. That, in turn, should improve performance of domestic banks, which
can additionally benefit from the spillover effects. This would suggest that it is more
difficult to improve performance of a domestic bank that is acquired in a country with
a high share of foreign banks. To control for this impact, we model the propensity
of being acquired by additionally introducing variables that capture the share of foreign banks in the country (Table 9, panel A). Then, we further differentiate between
share of greenfield and takeover banks, since banks with different modes of entry can
exert different competitive pressure. More specifically, Claeys & Hainz (2007) note
that competition on the banking market is stronger when a foreign bank enters via a
greenfield investment than via the acquisition.
Table 9: Results of the matching procedure for ROA and Market Share controlling
for a share of foreign banks, and shares of greenfield and takeover banks
ROA
Market share
No. of observations
-0.457
[0.915]
1.971*
[1.171]
2.174*
[1.241]
1.114
[0.985]
0.480
[0.960]
0.091
0.434
0.964*
[0.529]
1.546**
[0.655]
73
-0.216
[0.914]
2.019*
[1.169]
1.825*
[1.045]
1.362
[1.095]
0.546
[0.961]
0.206
[0.432]
1.157**
[0.520]
1.603***
[0.615]
Sample matched on Share Foreign
Acquisition year
One year later
Two years later
Three years later
69
61
54
Sample matched on Share Greenfield
and Takeover
Acquisition year
One year later
Two years later
Three years later
73
69
61
54
The table lists coefficients and bootstrapped standard errors (in parentheses) of the Difference in Difference methodology for estimating the impact of foreign acquisitions on ROA and Market Share. Panel
A presents the results of DID when the initial matching was performed with a lagged Share Foreign
variable added in the logit model, Panel B - with the lagged Share Greenfield and Share Takeover added
to the logit model. Neither variable was significant in the logit regressions. Definitions of variables are
provided in Table 2. ***, **, and * correspond to 1%, 5% and 10% significance levels.
33
CEPII, Working Paper No 2008 – 16
The results of this exercise are presented in panel B of Table 9. None of the three
variables enter significantly the logit regression. The results of treatment effects are
similar to the previous robustness check: the impact of foreign acquisition has a positive impact on both ROA and market share. We perform also other similar robustness
checks which involve augmenting a propensity model with variables that do not enter
significantly in our baseline model, such NIM, costs, or value of bilateral trade. The
results remain robust.
Another concern that might arises concerning our results is the fact that our methodology allows us to match banks in different countries. Therefore, there is a risk that
the observed differences in performance between takeover and control banks stem
not from positive impact of foreign acquisition, but from differences in macroeconomic conditions between countries of takeover and control banks. For example,
if macroeconomic conditions were more benign in countries where takeover banks
were located, this would allow these banks to be more profitable and grow faster
than control banks located in other countries. To test for this, we regress differences
in our performance measures between takeover and control banks on differences in
macroeconomic conditions between host countries of takeover and control banks. To
control for macroeconomic conditions, we include GDP growth, real interest rate,
inflation, as well as Herfindhal index to capture market concentration, and a ratio of
FDI and trade to GDP to control for openness of the economies. None of these variables turn out significant, indicating that our results stem from the impact of foreign
bank ownership and not from differences between countries.
9.
C ONCLUSIONS
The aim of this paper is to asses the impact of foreign acquisitions on the performance of banks operating in Central and Eastern Europe. We use a combination of
propensity score matching and difference-in-difference methodology to account for
the possible selection bias that is not controlled by standard regression techniques.
In the first part of our analysis we document that foreign banks preferred to acquire
large banks in CEECs, because it was time-consuming and expensive to gain market
power through a natural portfolio growth. As to the performance of target banks,
we show that acquired banks were on average less profitable but better capitalized
than institutions that remained in domestic hands. This reflects the situation that
local regulatory authorities decided to sell banks to foreign investors in the wake
of the crises when profits were low, but in some cases they recapitalized the banks
beforehand to render them more attractive to investors.
The above selection bias makes traditional regression techniques badly suited for the
analysis of post-acquisition performance and explains why most studies fail to pick
34
Inherited or earned? Performance of foreign banks in Central and Eastern Europe
up a significant impact of foreign bank ownership on takeover banks, and find it only
in the case of greenfield banks. Negative selection bias in bank performance makes
results biased downwards, because new foreign investors have to reform the acquired
bank just to make it comparable to local banks in terms of efficiency and profitability.
Positive selection bias in bank size, however, also influences findings downwards,
since larger banks always grow slower than small young ones.
Controlling for the selection bias, we analyze the post-takeover performance by employing difference-in-difference technique. We find that in the year of the acquisition,
foreign investors recapitalize the acquired bank. It takes one more year to achieve an
increase of profits, which comes from cutting costs and lowering loan loss provisions.
In theory, lower loan loss provisions can reflect better risk management techniques
or, alternatively, shifting to more transparent large clients, at the expanse of small entrepreneurs. These changes in the portfolio composition can also lead to higher costs
for domestic banks, because lending to opaque clients is based on soft information
and is very labor intensive. There is some evidence that all these explanations play
a role. Unfortunately, the BankScope data does not provide information which can
help us to answer these questions, and more research is needed to address this issue.
Another advantage of foreign bank ownership is lower cost of funds, which stems
from better reputation and superior access to international capital markets either directly or via the parent banks. We show that this lower cost of funds is passed on
to borrowers and, therefore, we do not observe an increase in net interest margin of
foreign banks in the post-acquisition period.
Two years after the acquisition, the market share of foreign banks starts to grow.
Since this happens after the improvements in banks’ performance, we can argue that
foreign banks succeeded to increase their market share due to their attractiveness
to clients. This would support the “efficiency ” hypothesis and would not cause
competition problems. Our results are contrary to findings for developed countries,
where foreign banks are more likely to sacrifice profits for growth.
Our paper contributes to our understanding of mechanisms through which foreign
investors affect the performance of the acquired banks. Our methodology allowed us
to pick up the improvements in performance which led to a higher market share of
foreign banks. Previous studies did not succeed to document these effects due to the
selection bias and due to the fact that it takes some transitional period for new owners
to reform an acquired institution. So, to answer the question posed in the title, we
can conclude that superior performance of foreign banks is not inherited but earned.
35
CEPII, Working Paper No 2008 – 16
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38
1♦
List of working papers released by CEPII
N°
Titre
Auteurs
2008-15 The Effect of Foreign Bank entry on the Cost of
Credit in Transition Economies. Which borrowers
benefit the most?
2008-14 Contagion in the Credit Default Swap Market:
the case of the GM and Ford Crisis in 2005
2008-13 Exporting to Insecure Markets: A Firm-Level
Analysis
H. Degryse,
O. Havrylchyk,
E. Jurzyk, S. Kozak
Virginie Coudert
Mathieu Gex
M. Crozet, P. Koenig
& V. Rebeyrol
2008-12 Social Competition and Firms' Location Choices
V. Delbecque,
I. Méjean & L.
Patureau
M. Daumal &
S. Zignago
G. Gaulier, J. Martin,
I. Méjean &
S. Zignago
A. de Saint Vaulry,
2008-11 Border Effects of Brazilian States
2008-10 International Trade Price Indices
2008-09 Base de données CHELEM – Commerce international
du CEPII
2008-08
2008-07
2008-06
2008-05
2008-04
2008-03
2008-02
2008-01
The Brain Drain between Knowledge-Based
Economies: the European Human Capital Outflow to
the US
Currency Misalignments and Exchange Rate Regimes
in Emerging and Developing Countries
The Euro and the Intensive and Extensive Margins of
Trade : Evidence from French Firm Level Data
On the Influence of Oil Prices on Economic Activity
and other Macroeconomic and Financial Variables
An Impact Study of the EU-ACP Economic
Partnership Agreements (EPAs) in the Six ACP
Regions
The Brave New World of Cross-Regionalism
Equilibrium Exchange Rates: a Guidebook for the
Euro-Dollar Rate
How Robust are Estimated Equilibrium Exchange
Rates? A Panel BEER Approach
A. Tritah
V. Coudert
& C. Couharde
A. Berthou
& L. Fontagné
V. Mignon
& F. Lescaroux
L. Fontagné,
D. Laborde
& C. Mitaritonna
A. Tovias
A. Bénassy-Quéré,
S. Béreau
& V. Mignon
A. Bénassy-Quéré,
S. Béreau
& V. Mignon
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Les documents de travail comportant * sont épuisés. Ils sont toutefois consultable sur le web CEPII.
2007-24
2007-23
2007-22
2007-21
2007-20
2007-19
2007-18
2007-17
2007-16
Testing the Finance-Growth Link: Is there a
Difference between Developed and Developing
Countries?
Labor Migration: Macroeconomic and Demographic
outlook for Europe and Neighborhood Regions
Economic Geography, Spatial Dependence and
Income Inequality in China
Does FDI in Manufacturing Cause FDI in Business
Services? Evidence from French Firm-Level Data
Bilateral Trade of Cultural Goods
China and India in International Trade: from Laggards
to Leaders?
How Remote is the Offshoring Threat ?
Costs and Benefits of Euro Membership:
a Counterfactual Analysis
Location Decisions and Minimum Wages
2007-14
MIRAGE, Updated Version of the Model for Trade
Policy Analysis Focus on Agriculture and Dynamics
Mondialisation des services : de la mesure à l'analyse
2007-13
How are wages set in Beijing?
2007-12
IMF Quotas at Year 2030
2007-11
FDI and Credit Constraints: Firm Level Evidence in
China
Fiscal Policy in Real Time
Global Ageing and Macroeconomic Consequences of
Demographic Uncertainty in a Multi-regional Model
The Effect of Domestic Regulation on Services Trade
Revisited
The Location of Domestic and Foreign Production
Affiliates by French Multinational Firms
Specialisation across Varieties within Products and
North-South Competition
Trade Costs and the Home Market Effect
2007-15
2007-10
2007-09
2007-08
2007-07
2007-06
2007-05
2007-04
The Impact of Regulations on Agricultural Trade:
Evidence from SPS and TBT Agreements
G. Dufrénot,
V. Mignon
& A. Péguin-Feissolle
V. Borgy
& X. Chojnicki
L. Hering
& S. Poncet
B. Nefussi
& C. Schwellnus
A.C. Disdier,
S.H.T. Tai,
L. Fontagné
& T. Mayer
F. Lemoine
& D. Ünal-Kesenci
K. Head, T. Mayer
& J. Ries
E. Dubois, J. Héricourt
& V. Mignon
I. Méjean
& L. Patureau
Y. Decreux
& H. Valin
I. Bensidoun
& D. Ünal-Kesenci
J. De Sousa
& S. Poncet
A. Bénassy-Quéré,
S. Béreau, Y. Decreux,
C. Gouel & S. Poncet
J. Héricourt
& S. Poncet
J. Cimadomo
J. Alho & V. Borgy
C. Schwellnus
T. Mayer, I. Méjean
& B. Nefussi
L. Fontagné, G. Gaulier
& S. Zignago
M. Crozet
& F. Trionfetti
A.-C. Disdier,
L. Fontagné
& M. Mimouni
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